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In machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling. [1] It is part of the families of probabilistic graphical models and variational Bayesian methods .
Hugging Face, Inc. is a Franco-American company that develops computation tools for building applications using machine learning. It is known for its transformers library built for natural language processing applications.
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
[64] [65] Released in 2022 on Hugging Face's Spaces platform, Craiyon (formerly DALL-E Mini until a name change was requested by OpenAI in June 2022) is an AI model based on the original DALL-E that was trained on unfiltered data from the Internet. It attracted substantial media attention in mid-2022, after its release due to its capacity for ...
Watsonx.ai is a platform that allows AI developers to leverage a wide range of LLMs under IBM's own Granite series and others such as Facebook's LLaMA-2, free and open-source model Mistral and many others present in Hugging Face community for a diverse set of AI development tasks.
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Researchers from Hugging Face and Carnegie Mellon University reported in a 2023 paper that generating one thousand 1024×1024 images using Stable Diffusion's XL 1.0 base model requires 11.49 kWh of energy and generates 1,594 grams (56.2 oz) of carbon dioxide, which is roughly equivalent to driving an average gas-powered car a distance of 4.1 ...